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Drone Mapping Software for Agriculture Development

  • Rating — 5 (21 votes)
  • by Tony
  • Updated on July 03, 2020
  • Read —
    12-13 minutes
drone for agricultural use

The world’s population is projected to hit 9 billion people by the end of 2050. Naturally, food consumption will rise accordingly. Experts suggest a nearly 70% growth in demand for agricultural products and this is an optimistic forecast considering the overall shortage of cultivated areas and climate change.

Such high demand is pushing agriculture industry to embrace innovations and look for new ways in order to overcome productivity obstacles. Drones are one of the solutions that is already here to intensify farmers’ production.

The agriculture drones market is expected to grow from USD 1.2 billion by 2019 to USD 4.8 billion by 2024 at a CAGR of 31.4%. The pressure on global food supply due to growing world population and increase in venture funding for the development of agriculture drones are a few of the key factors driving the growth of this market.

Field mapping to account for the largest share of agriculture drones market for precision farming during the forecast period. Field mapping helps look at the condition and health of crops across different soil types and management zones to portray crop health and yield potential.

It is expected that the agriculture drones market will grow a higher CAGR during the forecast period. This is due to high investments being done by the venture capitalists and investors in the start-up companies that suggest software and analytics to digitize the information collected by drones. Key sectors for investment are mapping, imaging, and data analytics software.

North America can take the main part of agriculture drone market during forecast period because of the exemption from the Federal Aviation Administration (FAA) under the part 107 rule which is leading to high adoption of drones in agriculture. This fact attracts investments by venture capitalists in the agriculture drones market.

Drone Mapping Software Market Prospects

a market value by industry agriculture

 

The Census of Agriculture numbers around 2.2 million farms in U.S. with a total area of 922 million acres. 88% of those households are small family farms with the average area of 230 acres. This is the best-targeted audience drone industry could ever wish to have.

Just look at this number: 1.85 million farms that can immediately benefit from agricultural drones and eager to do so because of hardening competition and demand increase. Based on these and other figures PwC estimates the market at $32.4 billion. Not bad for a start!

Another thing to mention: some analytics already site that 80% of the global drone industry revenues are related to agriculture.

The development of agricultural solutions is a complex process that requires an expert opinion. To get free consultation press bottom below

Benefits of Drones Used in Agriculture Sector

There is six Major Application of Drones for agricultural use:

  1. Soil and field analysis;
  2. Planting;
  3. Crop spraying;
  4. Irrigation;
  5. Health assessment;
  6. Geo-tagged monitoring.

As you may notice three of them (field analysis, monitoring, health assessment) are built around field mapping software instead of costly machinery. From an investment point of view, these fields grant a higher return of investment rate and better flexibility in terms of product development process.

Advantages of Farm Mapping Software

Soil and Field Analysis

Thermal image used to find water leaks

Thermal image used to find water leaks

Planting & Irrigation in AgroTech

The identification of field condition allows farmers to take informed actions, save on irrigation or enhance nitrogen-level management. Drones can acquire precise 3D volumetric data, which reveals hills and drainage points and save on the number of personnel required. Based on this data farmers can plan their planting pattern and distribute crops according to the specifics of the landscape.

Geo-Tagged Monitoring

Monitoring via drones

It must be acknowledged that vast field areas become the main stop factor that lowers or even completely negates the crop monitoring. Nevertheless, unpredictable weather conditions require from farmers to take immediate actions without waiting for a season to end. It is no longer possible to decide what went wrong based on after-effects and season statistics.

Crop spraying

A professional UAV give deep understanding of a crop’s growth, enabling agricultural specialists to identify issues at once, and better target their field scouting. Data collected over several years is able to improve planning and monitoring their jobs, for example, ditches and evolving fertiliser applications.

For example, drone use per growth stage (corn) Drone technology adds value throughout the growing season, from emergency and early growth assessments through to pre-harvest yield prediction.

Crop monitoring provides flexibility and allows farmers to adjust their strategy during a season and even within a month. Crop monitoring also allows farmers to reduce field maintenance costs and focus only on the most critical areas, thus saving their resources.

Previously, crop monitoring was possible only with the help of satellite imagery. Obviously, this service was extremely expensive, an image quality could suffer from weather conditions and resolution left much to be desired. Fortunately, the Unmanned Aerial Vehicles are here to become a better alternative.

GBKSOFT

Agricultural runoff from industrial fertilizer and pesticides is a major health concern. By checking on plant health and pinpointing troubled areas, drones produce valuable data that farmers can use to reduce chemical application by only administering chemicals in a very targeted manner.

Health Assessment

The health analysis is performed by gathering data from several sources via thermal, multispectral and infrared sensors. This way farmers can learn a sunlight absorption and transpiration rate of their crops. Further on one could apply NDVI mapping method in order to know the field’s health condition.

monitoring by Unmanned Aerial Vehicle

In essence, Normalized Difference Vegetation Index (NDVI) is a mapping method that reveals green portions on the map and indicates early warning based on the slight color deviations of the crops.

Frankly speaking, NDVI is well-known among industry players. What makes it different now is an image resolution and image acquisition speed that can be achieved, using drones instead of satellites. Commercial drones can acquire a much more detailed map and measure areas within centimeters as compared to meters. So drones are better and cheaper than satellites. 

“By having this information up-front farmers may be able to gain not $3,000 to $4,000 a ton but $5,000 a ton, depending on what the issue actually is.”

Jonathan Smith - Status Imaging Director

The drone technology can be also used to spot bacterial or fungal infections on trees. The health information can be gathered from multispectral images that track changes in plants and indicate their health. A swift response can save an entire orchard.

Don't let your chance to get a high-quality solution for agricultural business!

In addition, as soon as sickness is discovered, farmers can use remedies to get a more precise picture and track plant’s condition during treatment in order to identify the efficiency of medicine.

Precision Agriculture

DVI image

All those mapping practices are used as a foundation of a comprehensive farming management concept called – Precision Agriculture. Precision Agriculture gained decent popularity inside the industry and viewed as one of most promising trends.

The concept is based on observing, measuring and responding to inter- and intra-field variability in crops. If you need a deeper understanding, here’s a great article The Economist have published on this matter.

The goal is to distribute farm’s resources more efficiently and gain maximum yield of course. This is achieved by minimizing a variability of crop health within a single field, thus taking action point-wise.

Agriculture Mapping Software Functions

photo made by agriculture drone

Obviously, Precision Agriculture requires a lot of data. Moreover, it requires gathering data on a regular basis. And that is where drones mapping software comes in handy!

Technically, UAV drones can gather a wide variety of data just by capturing the imagery of livestock, fields, and specific plants. Here’s a rough list of info you can acquire from images:

  • Plant count, height.
  • Plant stress monitoring.
  • Leaf area indexing.
  • The presence of disease, nutrients, weeds.
  • Relative biomass estimation.
  • Yield monitoring.
  • Animals movement.
  • Tree classification.
  • Drought assessment.
  • 3D field surveying (elevations, holes, suitable water drainage points).

How Farm Mapping Software Works

Farm Mapping multi spectral and visual image by drone

Let’s start with the types of imagery that can be acquired by drones:

  • Visual.
  • Thermal/IR. This kind of sensors can see hotspots and measure land and plant temperature.Thermal sensors are also used to detect the water because of its cooler temperature signature which helps detecting drought or leak in irrigation.
  • Multispectral. Used for health assessment and normalized difference vegetation index.
  • LIDAR. Despite its high cost, it may be used once for initial 3D field surveying.
  • Hyperspectral data. The combination and overlaying of images from multiple channels used for a more in-depth analysis.

How Agricultural Drones and Software Can Measure Health

Mostly, agriculture software uses multi-spectral imagery to reveal health conditions. Based on imagery taken by agricultural drones those algorithms analyze changes of near-infrared light and visible light reflected by crops.

Specifically, the algorithm analyses the changes in the volume of green color on VIS image and NIR light. Roughly speaking, the more green and reflected light present, the better is the plant’s health.

dead stressed and healthy leaf

By using this data farmers can monitor health changes over time, calculating and tracking NDVI. The NDVI calculation principle is pretty much based on the same method. NDVI = (NIR-VIS)/(NIR+VIS).

Here is an example of the NDVI-processed image.
NDVI-processed image by drone app

That’s, basically, how agricultural health mapping software works.

Further useful UAV applications in AgroTech:

  • UAV / Drone based remote sensing for mapping & surveying.
  • UAV / Drone based industrial inspection, maintenance & repair of oil & gas platforms, assets, utilities, infrastructure & energy parks.
  • UAV / Drone based precision agriculture for crop, soil and irrigation monitoring.
  • UAV / Drone based structural analysis in assessment, archaeology & heritage monument inspection.
  • UAV / Drone based documentation with aerial imaging.
  • UAVs / Drones as first to respond in case of accident, fire or crisis.
  • UAV / Drone based flight dynamics & control theory research.
  • UAV / Drone based flight automation & reproduction.
  • UAV / Drone based computer vision & SLAM research.
  • UAV / Drone based swarming intelligence & networking.

Ready-made drone-mapping solutions for agriculture

As professional software engineers, we recommend you to opt for custom development whenever possible. But if you want to try some off-the-shelf solutions first, here are the most popular of them:

Useful Vocabulary

Photogrammetry – measuring done with the help of images, most commonly taken from air.

Thermography – imagery of the infrared spectrum of light. This kind of imagery shows areas of heat and have a quite number of commercial successful uses.

RGB Camera – the camera that is usually used in mapping. RGB cameras take a sample of Red, Green and Blue spectrums of light in order to create an image.

Point Cloud – a collection of points on the on an object’s or area’s surface used to create a 3D model. It is usually obtained from photogrammetric or LIDAR data.

Orthomosaic – Aerial images corrected for topographic relief to ensure that the scale of the image is uniform throughout.

GCP – Ground Control Point. A physical marker on the ground that guarantees the accuracy of a geographical map. GCP is located, using RTK (Real Time Kinematic) GPS coordinate. It properly aligns the whole map to ensure overall consistency.

RTK – Real Time Kinematic satellite navigation used to obtain centimeter-accurate GPS data.

In supporting precision farming, drones can do soil health scans, monitor crop health, assist in planning irrigation schedules, apply fertilizers, estimate yield data and provide valuable data for weather analysis.
To benefit from agricultural drone technology, you should make a careful preparation – from estimating business goals, to deciding on the proper hardware and drone software features. After all, drone technology development is a complex solution that requires a reliable drone hardware and software solutions provider. Following the decision to choose right subcontractors the discovery stage is the first step you can take to lay a solid foundation for the development of your app. It includes a functional specification, UX/UI design, etc that will give you a clear understanding of the end product. More information about discovery stage you may find here
Drones are inexpensive in comparison with satellite imagery and their data is more accurate, but there are things to consider before implementing drone solutions.

  1. Identifying goals. There are agriculture drones applications like field and crop monitoring, seed planting, cattle surveillance, etc. What kind of issue do you want to solve? Assess all your farm processes and concentrate on the main benefit most from using drones.
  2. In accordance with the law. Drone usage with commercial purposes should be done due to legal aspects so it is better involve a lawyer to take care of everything. Laws and rules for drone usage may vary depending on your country or state of residence. Register your drone if you have to and find out which types of drones you can legally use in your area.
  3. Considering the drone hardware Based on the tasks you want to reach, it is necessary to decide which hardware to equip your drone with. For example, for crop health monitoring, your drone will need an infrared camera. If you want it to estimate soil condition, it will need appropriate sensors, etc. And don’t forget about the drone capabilities that will depend on the tasks you have in mind.
  4. Selecting the type of drone software The collected data should be processed with agriculture drone software. There’s also a need navigation and flight management software, mapping. In some cases, ready-made, out-of-the-box software won’t work and you will need custom-made solutions that will meet all needs.
  5. Custom drone software At the start you need an understanding of the data collection, analysis, and visualization process. Also it is required deep knowledge of plant physiology to set the software algorithms to recognize certain patterns identifying plant health. You will also have to decide on the optimal image processing type, and on how your drone data will correlate with other metrics – like humidity, temperature, field topography, etc.

Bottom Line

It must be acknowledged that NDVI is the most popular index but not the most precise one. Hence, there are many other indexes that can be added to the agricultural mapping tool like CWSI and CCCI.

The development of such sophisticated system can add value to your agriculture apps and get you a better position on a competitive market. But this is another story that requires a deeper dive into the science of agriculture image processing.

Have a business idea on how drones usage can increase your farm productivity?

Tony Tony Sol is the business development manager of GBKSOFT, overseeing the production of all writings for both internal blog and external platforms. He is technical-driven person always looking for new benefits of merging business and software.

Comments (3)

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David Norriss
Oct 09, 2019 at 4:26 PM

I like how you said that precision agriculture is possible thanks to aerial imagery mapping practices. Farmers are a great example of the type of people that can be benefited by using aerial imagery acquisitions and mapping to know where they can start working more precisely. Thank you for helping me understand more about aerial imagery.

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Agrotechno
Apr 02, 2018 at 3:34 AM

Thanks for sharing about drone mapping software, I’m interested to purchase some software to improve my drone…

reply
Elena
Apr 03, 2018 at 2:25 PM
Agrotechno,

Hello! Building your own drone software is a good idea.
We can develop drone software from scratch for you. Our client manager will contact you via email so check out your inbox.

reply

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